5 papers
Optimal Transport-based Semantic Alignment for LLM-based Audio-Visual Speech Recognition
Xugang Lu, Peng Shen, Yu Tsao +1
Large language model (LLM)-based audio-visual speech recognition (LLM-AVSR) has recently demonstrated strong robustness in adverse acoustic environments by leveraging complementary…
Beyond Acoustic Prefixes: Persistent Grounding in Serialized Acoustic Memory for LLM-Based Multi-Talker Speech Recognition
Hao Shi, Yuan Gao, Xugang Lu +1
Large Language Models (LLMs) are effective decoders for Serialized Output Training (SOT) in two-talker automatic speech recognition (ASR), but their performance degrades substantia…
New Insights into Optimal Alignment of Acoustic and Linguistic Representations for Knowledge Transfer in ASR
Xugang Lu, Peng Shen, Hisashi Kawai
Aligning acoustic and linguistic representations is a central challenge to bridge the pre-trained models in knowledge transfer for automatic speech recognition (ASR). This alignmen…
Cross-modal Knowledge Transfer Learning as Graph Matching Based on Optimal Transport for ASR
Xugang Lu, Peng Shen, Yu Tsao +1
Transferring linguistic knowledge from a pretrained language model (PLM) to acoustic feature learning has proven effective in enhancing end-to-end automatic speech recognition (E2E…
Retrieval-Augmented Speech Recognition Approach for Domain Challenges
Peng Shen, Xugang Lu, Hisashi Kawai
Speech recognition systems often face challenges due to domain mismatch, particularly in real-world applications where domain-specific data is unavailable because of data accessibi…